High-resolution image reconstruction is an important problem in image processing. In general, the blurring matrices are ill-conditioned, and it is necessary to compute a regularized solution. Moreover, error exists not only in the blurred image but also the blurring matrix, thus the total least squa
✦ LIBER ✦
Implementation of the regularized structured total least squares algorithms for blind image deblurring
✍ Scribed by N. Mastronardi; P. Lemmerling; A. Kalsi; D.P. O’Leary; S. Van Huffel
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 406 KB
- Volume
- 391
- Category
- Article
- ISSN
- 0024-3795
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By use of rotation angle method a direct algorithm is derived, which determines the least-squares superposition that matches two sets of atomic coordinates. The program based on this algorithm runs fast. The solution obtained by this algorithm cannot be trapped by any local minimum. Testing examples